A novel paradigm for feedback control in LPBF: layer-wise correction for overhang structures

Abstract

In laser powder bed fusion (LPBF), it is common practice to select process parameters to achieve high density parts starting from simple geometries such as cubes or cylinders. However, additive manufacturing is usually adopted to produce very complex geometries, where parameters should be tuned locally, depending on the local features to be processed. In fact, geometrical features, such as overhangs, acute corners, and thin walls may lead to over- or under-heating conditions, which may result in geometrical inaccuracy, high roughness, volumetric errors (i.e., porosity) or even job failure due to surface collapse. This work proposes a layer-wise control strategy to improve the geometrical precision of overhanging regions using a coaxial melt pool monitoring system. The melt-pool images acquired at each layer are used in a control-loop to adapt the process parameters locally at the next layer in order to minimize surface defects. In particular, the laser duty cycle is used as a controllable parameter to correct the energy density. This work presents the main architecture of the proposed approach, the control strategy and the experimental procedure that need to be applied to design the control parameters. The layer-wise control strategy was tested on AISI 316L stainless steel using an open LPFB platform. The results showed that the proposed layer-wise control solution results in a constant melt pool observed via the laser heated area size starting from the second layer onward, leading to a significant improvement in the geometrical accuracy of 5 mm-long bridge geometries.

Keywords

Closed-loop control / Melt pool monitoring / Defect correction / Pulsed-wave emission

References

[1] Grasso M, Colosimo BM. Process defects and in situ monitoring methods in metal powder bed fusion: a review. Meas Sci Technol, 2017, 28(4): 044005.

[2] Tapia G, Elwany A. A review on process monitoring and control in metal-based additive manufacturing. J Manuf Sci Eng Trans ASME, 2014, 136(6): 060801.

[3] Pavlov M, Doubenskaia M, Smurov I. Pyrometric analysis of thermal processes in SLM technology. Phys Procedia, 2010, 5(PART 2): 523-531.

[4] Lott P, Schleifenbaum H, Meiners W, et al. Design of an optical system for the in situ process monitoring of selective laser melting (SLM). Phys Procedia, 2011, 12(PART 1): 683-690.

[5] Eschner N, Weiser L, Häfner B, et al. Development of an acoustic process monitoring system for selective laser melting (SLM). Solid Free Fabr Symp, 2018, 2017: 2097-2117.

[6] Fisher BA, Lane B, Yeung H, et al. Toward determining melt pool quality metrics via coaxial monitoring in laser powder bed fusion. Manuf Lett, 2018, 15: 119-121.

[7] Colosimo BM, Grossi E, Caltanissetta F, et al. Penelope: a novel prototype for in situ defect removal in LPBF. OM, 2020, 72(3): 1332-1339.

[8] Caltanissetta F, Grasso M, Petrò S, et al. Characterization of in-situ measurements based on layerwise imaging in laser powder bed fusion. Addit Manuf, 2018, 24(8): 183-199.

[9] Kanko JA, Sibley AP, Fraser JM. In situ morphology-based defect detection of selective laser melting through inline coherent imaging. J Mater Process Technol, 2016, 231: 488-500.

[10] Smith RJ, Hirsch M, Patel R, et al. Spatially resolved acoustic spectroscopy for selective laser melting. J Mater Process Technol, 2016, 236: 93-102.

[11] Martin AA, et al. Dynamics of pore formation during laser powder bed fusion additive manufacturing. Nat Commun, 2019, 10(1): 1-10.

[12] Paulson NH, Gould B, Wolff SJ, et al. Correlations between thermal history and keyhole porosity in laser powder bed fusion. Addit Manuf, 2020, 34: 101213.

[13] Grasso M, Laguzza V, Semeraro Q, et al. In-process monitoring of selective laser melting: spatial detection of defects via image data analysis. J Manuf Sci Eng, 2016, 139(5): 051001.

[14] Finazzi V, Demir AG, Biffi CA, et al. Design rules for producing cardiovascular stents by selective laser melting: geometrical constraints and opportunities. Procedia Struct Integr, 2019, 15: 16-23.

[15] Khairallah SA, Martin AA, Lee JRI, et al. Controlling interdependent meso-nanosecond dynamics and defect generation in metal 3D printing. Science, 2020, 368(6491): 660-665.

[16] Caprio L, Demir AG, Previtali B. Influence of pulsed and continuous wave emission on melting efficiency in selective laser melting. J Mater Process Tech, 2018, 266: 429-441.

[17] Demir AG, Previtali B. Additive manufacturing of cardiovascular CoCr stents by selective laser melting. Mater Des, 2017, 119: 338-350.

[18] Demir AG, Colombo P, Previtali B. From pulsed to continuous wave emission in SLM with contemporary fiber laser sources: effect of temporal and spatial pulse overlap in part quality. Int J Adv Manuf Technol, 2017, 91(5/8): 2701-2714.

[19] Demir AG, Mazzoleni L, Caprio L, et al. Complementary use of pulsed and continuous wave emission modes to stabilize melt pool geometry in laser powder bed fusion. Opt Laser Technol, 2019, 113: 15-26.

[20] Hofman JT, Pathiraj B, Van Dijk J, et al. A camera based feedback control strategy for the laser cladding process. J Mater Process Tech, 2012, 212(11): 2455-2462.

[21] Song L, Mazumder J. Feedback control of melt pool temperature during laser cladding process. IEEE Trans Control Syst Technol, 2011, 19(6): 1349-1356.

[22] Duflou JR, Sichani EF, De Keuster J et al (2009) Developement of a real time monitoring and adaptive control for laser flame cutting. J Laser Appl 2009:527–536

[23] Postma S, Aarts RGKM, Meijer J et al (2018) Penetration control in laser welding of sheet metal using optical sensors. Proc of ICALEO 2001:1083–1092

[24] Kempen KJP, Vrancken B, Thijs L et al (2013) Lowering thermal gradients in selective laser melting by pre-heating the baseplate. Solid Free Fabr Symp Proc 24:131–139

[25] Demir AG, Previtali B. Investigation of remelting and preheating in SLM of 18Ni300 maraging steel as corrective and preventive measures for porosity reduction. Int J Adv Manuf Technol, 2017, 93(5): 2697-2709.

[26] Li Z, Xu R, Zhang Z, et al. The influence of scan length on fabricating thin-walled components in selective laser melting. Int J Mach Tools Manuf, 2018, 126: 1-12.

[27] Zeng K, Pal D, Gong HJ, et al. Comparison of 3DSIM thermal modelling of selective laser melting using new dynamic meshing method to ANSYS. Mater Sci Technol, 2015, 31(8): 945-956.

[28] Bugatti M, Semeraro Q. Limitations of the inherent strain method in simulating powder bed fusion processes. Addit Manuf, 2018, 23: 329-346.

[29] Druzgalski CL, Ashby A, Guss G et al (2020) Process optimization of complex geometries using feed forward control for laser powder bed fusion additive manufacturing. Addit Manuf 34:101169. https://doi.org/10.1016/j.addma.2020.101169

[30] Mazzoleni L, Demir AG, Caprio L et al (2019) Real-time observation of melt pool in selective laser melting: spatial, temporal and wavelength resolution criteria. IEEE Trans Instrum Meas 69(4):1179–1190

[31] Renken V, von Freyberg A, Schünemann K, et al. In-process closed-loop control for stabilising the melt pool temperature in selective laser melting. Prog Addit Manuf, 2019, 4: 411-421.

[32] Yeung H, Lane BM, Donmez MA, et al. Implementation of advanced laser control strategies for powder bed fusion systems. Procedia Manuf, 2018, 26: 871-879.

[33] Craeghs T, Bechmann F, Berumen S, et al. Feedback control of layerwise laser melting using optical sensors. Phys Proc, 2010, 5(PART 2): 505-514.

[34] Mercelis P, Kruth JP, Van Vaerenbergh J (2007) Feedback control of selective laser melting. Proc 15th Int Symp Electromachining, ISEM 2007, pp 421–426

[35] Hirsch M, et al. Assessing the capability of in-situ nondestructive analysis during layer based additive manufacture. Addit Manuf, 2017, 13: 135-142.

[36] Demir AG, De Giorgi C, Previtali B. Design and implementation of a multisensor coaxial monitoring system with correction strategies for selective laser melting of a maraging steel. J Manuf Sci Eng Trans ASME, 2018, 140(4): 041003.

[37] Lane B, Heigel J, Ricker RE et al (2020) Measurements of melt pool geometry and cooling rates of individual laser traces on IN625 bare plates. Integr Mater Manuf Innov 9(1):16–30

[38] Pacher M, Mazzoleni L, Caprio L, et al. Estimation of melt pool size by complementary use of external illumination and process emission in coaxial monitoring of selective laser melting. J Laser Appl, 2019, 31(2): 022305.

[39] Mazzoleni L, Caprio L, Pacher M, et al. External illumination strategies for melt pool geometry monitoring in SLM. JOM, 2018, 71: 928-937.

[40] Adnan M, Lu Y, Jones A et al (2018) Application of the fog computing paradigm to additive manufacturing process monitoring and control. T Emerg Telecommun T 29(4):1–14

[41] Clijsters S, Craeghs T, Buls S, et al. In situ quality control of the selective laser melting process using a high-speed, real-time melt pool monitoring system. Int J Adv Manuf Technol, 2014, 75(5): 1089-1101.

[42] Vasileska E, Demir AG, Colosimo BM, et al. Layer-wise control of selective laser melting by means of inline melt pool area measurements. J Laser Appl, 2020, 32(2): 022057.

[43] Hooper PA. Melt pool temperature and cooling rates in laser powder bed fusion. Addit Manuf, 2018, 22: 548-559.

[44] Heigel JC, Lane BM. Measurement of the melt pool length during single scan tracks in a commercial laser powder bed fusion process. J Manuf Sci Eng Trans ASME, 2018, 140(5): 051012-10.1115/1.4037571.

[45] Spierings AB, Levy G (2009) Comparison of density of stainless steel 316L parts produced with selective laser melting using different powder grades. 20th Annu Int Solid Free Fabr Symp SFF, pp 342–353

[46] Lane B, Moylan S, Whitenton EP, et al. Thermographic measurements of the commercial laser powder bed fusion process at NIST. Rapid Prototyp J, 2016, 22(5): 778-787.

[47] Sih SS, Barlow JW. The prediction of the emissivity and thermal conductivity of powder beds. Part Sci Technol, 2004, 22(4): 427-440.

[48] Fischer P, Romano V, Weber HP, et al. Sintering of commercially pure titanium powder with a Nd: YAG laser source. Acta Mater, 2003, 51(6): 1651-1662.

[49] Phillips T, Ricker T, Fish S, et al. Design of a laser control system with continuously variable power and its application in additive manufacturing. Addit Manuf, 2020, 34: 101173

Funding

Ministero dell’Istruzione, dell’Università e della Ricerca http://dx.doi.org/10.13039/501100003407(LIS4.0)